Forward Deployed Engineer

Role :

Forward Deployed Engineer (FDE) specializing in Gemini Enterprise, Agentic AI, and Multi-Agent Systems.

Responsibilities :

- Design, develop, and deploy production-grade Multi-Agent Systems (MAS) and agentic workflows using Gemini Enterprise.

- Identify need for Pro Code Vs No Code design based on customer's problem statement and data sources.

- Design and deploy custom agents using the Agent Development Kit (ADK), and Agent Platform AI Reasoning Engine and integrate with Gemini Enterprise.

- Build native integrations across the Google Workspace Ecosystem (Docs, Drive, Gmail, Calendar, Meet) and NotebookLM for grounded enterprise research, document automation, and conversational discovery.

- Architect scalable short-term session storage, conversation state persistence, and long-term memory architectures across multi-agent interactions.

- Implement end-to-end authentication and authorization perimeters for agents, Google Cloud services, and 3rd-party SaaS integrations (e.g., Microsoft Entra ID / M365, Salesforce, Atlassian) using IAM, OAuth 2.0, OIDC, and service identities.

- Enforce fine-grained Access Control Lists (ACLs), user/group permission inheritance, and data governance policies to ensure agents strictly adhere to enterprise access boundaries.

- Utilize developer tooling including Agent CLI and Antigravity for local rapid prototyping, testing, emulation, distributed tracing, and root cause analysis (RCA).

- Architect Human-in-the-Loop (HITL) workflows, ensuring seamless Interrupt and Resume patterns between autonomous agents and human experts for critical decision points.

- Build and maintain automated CI/CD pipelines (e.g., Cloud Build, GitHub Actions, GitLab CI) to manage versioned agent deployments, automated testing, and continuous regression evaluations.

- Implement advanced reasoning patterns such as Chain-of-Thought (CoT), ReAct, Plan-and-Solve, and Self-Reflection to enhance agent reliability.

- Establish quantitative evaluation frameworks to measure agent trajectories, tool invocation precision/recall, and reasoning faithfulness.

- Collaborate directly with client engineering and architecture teams to deploy, validate, and operationalize enterprise agentic AI solutions in client environments.

Must-Have Skills :

- Core Engineering & Frameworks : Strong proficiency in Python with production-level software engineering practices, along with deep, hands-on experience building multi-agent systems using Google ADK (Agent Development Kit) or comparable agentic frameworks.

- Gemini & Workspace Ecosystem : Solid hands-on experience deploying and customizing Gemini Enterprise, NotebookLM, and integrating with the broader Google Workspace Ecosystem (APIs, Add-ons, Drive/Docs connectors).

- Memory & State Architecture : Demonstrated expertise in managing agent session state, short-term context caching, and durable long-term memory backends (vector databases, relational/NoSQL session stores).

- Third Party Tools : Experience with MCP Connectors to securely integrate core third-party platforms (e.g., iManage, NetDocuments, Relativity, DocuSign, MS Office Suite, Sharepoint, JIRA) with Gemini Enterprise.

- Auth & Security : Strong understanding of authentication and authorization protocols (IAM, OAuth 2.0, OIDC, Service Accounts, Workload Identity Federation) across Google Cloud and 3rd-party SaaS platforms (Microsoft Entra ID, Salesforce, Atlassian).

- ACLs & Permissions : Deep working knowledge of enterprise Access Control Lists (ACLs), identity federation, permission trimming, and role-based access control (RBAC) across heterogeneous data sources.

- Developer Tooling : Proficiency in developer tooling such as Agent CLI and Antigravity for local simulation, debugging, prompt engineering, and execution graph tracing.

- CI/CD & DevOps : Proven track record of configuring and maintaining automated CI/CD pipelines (Cloud Build, GitHub Actions) for agent containerization, deployment, and test automation.

- Evaluation & Debugging : Practical knowledge of AI evaluation methodologies, trajectory analysis, and performing root cause analysis (RCA) on agent execution failures, tool errors, and prompt regressions.

- Client Collaboration : Strong technical communication, consulting acumen, and client-facing collaboration skills within an Agile environment.

Skills

Python, Agentic AI, Forward Deployment Engineering, Configuration Management, DevOps, AIOps, SaaS, Google Cloud Platform, CI/CD Pipeline